As enterprises accumulate ever greater amounts of data on their transactions, processes, products, and operations, online analytical processing has become an essential part of doing business. The number of tools and techniques addressing analytical processing has grown, enabling data analysts to quickly analyze and navigate through vast complex collections of data.
By conventional practice, online analytical processing is traditionally performed on data that is separate from live transactional data. Accordingly, although current approaches provide a wide variety of functionality, they result in complexities related to mapping and persistence. There is therefore room for improvement.